Litcius/Paper detail

An LSTM based architecture to relate speech stimulus to EEG

Mohammad Jalilpour Monesi, Bernd Accou, Jair Montoya-Martínez, Tom Francart, Hugo Van hamme

2020Lirias (KU Leuven)55 citationsDOIOpen Access PDF

Abstract

sponsorship: The work is funded by KU Leuven Special Research Fund C24/18/099 (C2 project to Tom Francart and Hugo Van hamme)This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 637424, ERC starting Grant to Tom Francart).) (KU Leuven Special Research Fund|C24/18/099, European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme|637424)

Topics & Concepts

Computer scienceSpeech recognitionElectroencephalographyConvolutional neural networkArtificial intelligenceDecoding methodsPattern recognition (psychology)EmbeddingContext (archaeology)AlgorithmNeurosciencePsychologyPaleontologyBiologyEEG and Brain-Computer InterfacesNeural dynamics and brain functionBlind Source Separation Techniques
An LSTM based architecture to relate speech stimulus to EEG | Litcius